Authors: Anu Taneja; Anuja Arora
Addresses: Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India ' Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India
Abstract: Recommendation systems have been well established to reduce the problem of information overload and have become one of the most valuable tools applicable to different domains like computer science, mathematics, psychology, etc. The initial interest to write this survey is composing a concise research paper on the key motivation behind the various existing recommender systems and their techniques used in various domains. In this paper, prioritisation of recommendation keywords is presented in form of weighted keyword network along with keywords associations according to their usage in reference section literature. Consequently, this paper provides comprehensive details of various public datasets, their corresponding techniques, comparative analysis of existing recommendation approaches based on faced challenges and performance measures are examined. This study will help the researchers and academicians in quickly understanding the existing work and in planning future recommendation studies for designing a unified and coherent recommender system.
Keywords: recommender systems; keyword timeline review; keyword network; memory-based approach; model-based approach; hybrid filtering; performance measures; open issues; web technology; research trends.
International Journal of Web Engineering and Technology, 2018 Vol.13 No.2, pp.123 - 186
Published online: 30 Jun 2018 *Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article